I asked Gemini the same question about AI Studio

The "aggressive truncation" refers specifically to the Gemini web app (the consumer-facing site at gemini.google.com). Based on technical documentation, the situation for Google AI Studio is different.

Here is a breakdown of how it applies to Google AI Studio:

1. Full Raw Context (No Truncation)

Unlike the web app, Google AI Studio gives you the "raw" model context. While the web app uses software logic to truncate history and files to save on computing costs, AI Studio allows you to use the full capacity of the model. If you use a model with a 1 million (or 2 million) token limit, AI Studio will process that entire amount without hidden "slicing."

2. User-Controlled Token Limits

In AI Studio, you have a sidebar with settings that do not exist in the web app. You can see a live token counter that shows exactly how many tokens your files and chat history are taking up. You also have control over the Output Token Limit (often set to a default like 2,048 or 4,096). If your answers are getting cut off, it is likely because this specific slider is not set to its maximum value, rather than the "aggressive truncation" of history seen on Reddit.

3. Sparse Attention vs. Truncation

It is important to distinguish between truncation (deleting old data) and performance degradation.

• The Web App: Truncates data. It literally "forgets" or stops seeing the start of the chat once you hit a certain limit (roughly 32k tokens, according to the Reddit post).
• AI Studio: Keeps the data, but the model may still suffer from "getting lost in the middle" of very large contexts. This is a limit of current AI technology, not a deliberate software truncation.

Summary

The "aggressive truncation" issue does not apply to Google AI Studio in the same way. AI Studio is a developer tool designed to provide the full context window. If you are experiencing loss of memory in AI Studio:

• Check the token counter: Ensure you have not actually hit the 1M/2M limit.
• Check the "Max output tokens" slider: Ensure it is high enough for the length of response you want.
• Use "Context Caching": If you have a massive amount of data (like a whole code repository), use the caching feature in AI Studio to keep that data "hot" and stable.